期刊
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
卷 67, 期 11, 页码 5856-5871出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2021.3124980
关键词
Balancing; contraction; controller reduction; model reduction; nonlinear systems
资金
- JSPS KAKENHI [JP21H04875, JP21K14185]
This article aims to develop computationally tractable methods for nonlinear model/controller reduction. It studies the incremental properties in the GD balancing framework and proposes GD LQG balancing and GD H-infinity balancing as controller reduction methods for nonlinear systems.
In this article, we aim at developing computationally tractable methods for nonlinear model/controller reduction. Recently, model reduction by generalized differential (GD) balancing has been proposed for nonlinear systems with constant input-vector fields and linear output functions. First, we study incremental properties in the GD balancing framework. Next, based on these analyses, we provide GD linear quadratic Gaussian (LQG) balancing and GD H-infinity-balancing as controller reduction methods for nonlinear systems by focusing on linear feedback and observer gains. Especially for GD H-infinity-balancing, we clarify when the closed-loop system consisting of the full-order system and a reduced-order controller is exponentially stable. All provided methods for controller reduction can be relaxed to linear matrix inequalities (LMIs).
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